An Exploratory Study of Quality of Life and Its Relationship with Academic Performance among Students in Medical and other Health Professions
Bibliographic record
Abstract
Quality of life (QOL) is a broader concept which represents experiences, states, appraisals, behaviors, capacities and emotional reactions to circumstances. The study aimed to evaluate the differences in various domains of QOL among the students of five schools (medicine, dentistry, veterinary medicine, pharmacy and nursing) and an optometry unit in the Faculty of Medical Sciences, Trinidad and Tobago. Further, the study evaluated the factors (sociodemographic variables and academic performance) predictive of physical, psychological, social and environment domains of quality of life. The research tool consisted of a validated questionnaire which had two sections; (1) sociodemographics inclusive of students’ cumulative grade point average and (2) the shorter version of WHO quality of life (WHOQOL-BREF). The data were transformed into a linear scale and exported into the IBM SPSS version 24 where t-tests, one-way ANOVA and stepwise regression were performed. Of the total 535 participants, most 383 (71.6%) were females. While comparing the differences in the domains of QOL that existed based on the schools (professions) they were enrolled, significant differences were recorded for physical (p < 0.05), psychological (p < 0.05) social (p < 0.05) and environmental domains (p < 0.05). Though the domains of physical health, psychological health and environment showed a significant association with the academic performance of students, the social domain had no such relationship. The overall quality of life has a positive connection with the academic performance of students in medical and health professions. Therefore, universities and all stakeholders involved in health professions need to play a critical role to ensure the students in health professions maintain a high QOL. At the same time, there is a great need for extra attention for students who showed poor academic performance in the previous semester to bring them on track.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".